The benefits of virtual learning webinars to both low- and high-income countries.

The coronavirus disease 2019 (COVID-19) pandemic has brought about many changes in the relationships between high-income countries and partner organisations in low- or low-middle-income countries, such as predominate in sub-Saharan Africa. Medicine, surgery and in particular urology is no exception to the changes that COVID-19 has demanded. Urolink represents the British Association of Urological Surgeons (BAUS) on the global urology stage and has been deleteriously impacted by the pandemic. Education, one of the pillars of Urolink's founding philosophies, has conventionally been delivered by face-to face teaching, training, or mentoring by UK urologists at their host's site outside of the UK. As a consequence of the inability to travel due to the pandemic, BAUS Urolink has evolved a virtual on-line webinar package evolved by, and delivered between, urologists in Lusaka, Zambia, and various centres in the UK. The aim was to deliver curricular-based educational topics to trainees in both countries. This programme has generated a number of live webinars and archived recordings during the pandemic that has proven accessible and educationally acceptable to trainees in the UK and Zambia. This webinar series has also generated relationships between young urologists on different continents, given each a different view of healthcare delivery outside of their country of origin at no appreciable cost, and would appear to be an educational mechanism that is durable for, and applicable to, a wider participation in the post-pandemic world.

Development and validation of prognosis model of mortality risk in patients with COVID-19.

This study aimed to identify clinical features for prognosing mortality risk using machine-learning methods in patients with coronavirus disease 2019 (COVID-19). A retrospective study of the inpatients with COVID-19 admitted from 15 January to 15 March 2020 in Wuhan is reported. The data of symptoms, comorbidity, demographic, vital sign, CT scans results and laboratory test results on admission were collected. Machine-learning methods (Random Forest and XGboost) were used to rank clinical features for mortality risk. Multivariate logistic regression models were applied to identify clinical features with statistical significance. The predictors of mortality were lactate dehydrogenase (LDH), C-reactive protein (CRP) and age based on 500 bootstrapped samples. A multivariate logistic regression model was formed to predict mortality 292 in-sample patients with area under the receiver operating characteristics (AUROC) of 0.9521, which was better than CURB-65 (AUROC of 0.8501) and the machine-learning-based model (AUROC of 0.4530). An out-sample data set of 13 patients was further tested to show our model (AUROC of 0.6061) was also better than CURB-65 (AUROC of 0.4608) and the machine-learning-based model (AUROC of 0.2292). LDH, CRP and age can be used to identify severe patients with COVID-19 on hospital admission.

Impact of COVID-19 outbreak on posttraumatic stress in patients with psychiatric illness.

The present study aimed to examine the prevalence of posttraumatic stress response in reaction to the COVID-19, including posttraumatic-stress-disorder-like symptoms (PTSD-like symptoms) and depressive symptoms, among patients with pre-existing psychiatric illness. The socio-demographic and psychological correlates of PTSD-like symptoms were also examined. A total of 193 participants were recruited. More than 45% of the respondents reported significant PTSD-like symptoms related to the COVID-19; this group of patients also had a high level of pandemic-related depressive symptoms. High level of PTSD-like symptoms were predicted by rumination on concerns about the outbreak of COVID-19 and feeling of social isolation. They were also associated with hypervigilance to cues related to the pandemic. Our results suggested that the pandemic had taken a psychological toll on people living with psychiatric illness. Further research is needed to understand the development and mechanism of traumatic stress reaction in response to a prolonged infectious disease outbreak among this vulnerable population. Clinical attention is also called to mitigate the psychiatric sequalae of the pandemic in this vulnerable group of people.

Clinical Manifestation and Neonatal Outcomes of Pregnant Patients With Coronavirus Disease 2019 Pneumonia in Wuhan, China.

BACKGROUND: Clinical manifestation and neonatal outcomes of pregnant women with coronavirus disease 2019 (COVID-19) were unclear in Wuhan, China. METHODS: We retrospectively analyzed clinical characteristics of pregnant and nonpregnant women with COVID-19 aged from 20 to 40, admitted between January 15 and March 15, 2020 at Union Hospital, Wuhan, and symptoms of pregnant women with COVID-19 and compared the clinical characteristics and symptoms to historic data previously reported for H1N1. RESULTS: Among 64 patients, 34 (53.13%) were pregnant, with higher proportion of exposure history (29.41% vs 6.67%) and more pulmonary infiltration on computed tomography test (50% vs 10%) compared to nonpregnant women. Of pregnant patients, 27 (79.41%) completed pregnancy, 5 (14.71%) had natural delivery, 18 (52.94%) had cesarean section, and 4 (11.76%) had abortion; 5 (14.71%) patients were asymptomatic. All 23 newborns had negative reverse-transcription polymerase chain results, and an average 1-minute Apgar score was 8-9 points. Pregnant and nonpregnant patients show differences in symptoms such as fever, expectoration, and fatigue and on laboratory tests such as neurophils, fibrinogen, D-dimer, and erythrocyte sedimentation rate. Pregnant patients with COVID-19 tend to have more milder symptoms than those with H1N1. CONCLUSIONS: Clinical characteristics of pregnant patients with COVID-19 are less serious than nonpregnant. No evidence indicated that pregnant women may have fetal infection through vertical transmission of COVID-19. Pregnant patients with H1N1 had more serious condition than those with COVID-19.

In-hospital cardiac arrest outcomes among patients with COVID-19 pneumonia in Wuhan, China.

OBJECTIVE: To describe the characteristics and outcomes of patients with severe COVID-19 and in-hospital cardiac arrest (IHCA) in Wuhan, China. METHODS: The outcomes of patients with severe COVID-19 pneumonia after IHCA over a 40-day period were retrospectively evaluated. Between January 15 and February 25, 2020, data for all cardiopulmonary resuscitation (CPR) attempts for IHCA that occurred in a tertiary teaching hospital in Wuhan, China were collected according to the Utstein style. The primary outcome was restoration of spontaneous circulation (ROSC), and the secondary outcomes were 30-day survival, and neurological outcome. RESULTS: Data from 136 patients showed 119 (87.5%) patients had a respiratory cause for their cardiac arrest, and 113 (83.1%) were resuscitated in a general ward. The initial rhythm was asystole in 89.7%, pulseless electrical activity (PEA) in 4.4%, and shockable in 5.9%. Most patients with IHCA were monitored (93.4%) and in most resuscitation (89%) was initiated <1 min. The average length of hospital stay was 7 days and the time from illness onset to hospital admission was 10 days. The most frequent comorbidity was hypertension (30.2%), and the most frequent symptom was shortness of breath (75%). Of the patients receiving CPR, ROSC was achieved in 18 (13.2%) patients, 4 (2.9%) patients survived for at least 30 days, and one patient achieved a favourable neurological outcome at 30 days. Cardiac arrest location and initial rhythm were associated with better outcomes. CONCLUSION: Survival of patients with severe COVID-19 pneumonia who had an in-hospital cardiac arrest was poor in Wuhan.